82 citations · 281 across the 31 of their papers we have counts for
11 papers · 1 filter
Efficient Decoding of Compositional Structure in Holistic Representations
Denis Kleyko, Connor Bybee, Ping-Chen Huang +4
We investigate the task of retrieving information from compositional distributed representations formed by Hyperdimensional Computing/Vector Symbolic Architectures and present nove…
Learning and generalization of compositional representations of visual scenes
E. Paxon Frady, Spencer Kent, Quinn Tran +3
Complex visual scenes that are composed of multiple objects, each with attributes, such as object name, location, pose, color, etc., are challenging to describe in order to train n…
Deep Learning in Spiking Phasor Neural Networks
Connor Bybee, E. Paxon Frady, Friedrich T. Sommer
Spiking Neural Networks (SNNs) have attracted the attention of the deep learning community for use in low-latency, low-power neuromorphic hardware, as well as models for understand…
Integer Factorization with Compositional Distributed Representations
Denis Kleyko, Connor Bybee, Christopher J. Kymn +5
In this paper, we present an approach to integer factorization using distributed representations formed with Vector Symbolic Architectures. The approach formulates integer factoriz…
Cellular Automata Can Reduce Memory Requirements of Collective-State Computing
Denis Kleyko, E. Paxon Frady, Friedrich T. Sommer
Various non-classical approaches of distributed information processing, such as neural networks, computation with Ising models, reservoir computing, vector symbolic architectures,…
Variable Binding for Sparse Distributed Representations: Theory and Applications
E. Paxon Frady, Denis Kleyko, Friedrich T. Sommer
Symbolic reasoning and neural networks are often considered incompatible approaches. Connectionist models known as Vector Symbolic Architectures (VSAs) can potentially bridge this…